Dry season forage assessment across senegalese rangelands using earth observation data - Archive ouverte HAL Access content directly
Journal Articles Frontiers in Environmental Science Year : 2022

Dry season forage assessment across senegalese rangelands using earth observation data

(1, 2) , (1, 2) , (3) , (1, 2) , (4, 5) , (6, 7) , (7) , (8) , (9) , (10, 11) , (12) , (10, 11) , (1) , (1, 2)
1
2
3
4
5
6
7
8
9
10
11
12

Abstract

Strengthening of feed security in the Sahel is urgently needed given the climate change and growing human population. A prerequisite to this is sustainable use of rangeland forage resources for livestock. Many studies have focused on the assessment of rangeland resources during the rainy season, while only a few have focused on the dry season which is the longest and most demanding period for livestock in Sahelian rangelands. The objective of this study is to develop remote sensing-based models for estimating dry season forage vegetation mass. To that end, 29 vegetation indices calculated from each of the MODIS-MCD43A4 (500 m), Landsat-8 (30 m), and Sentinel-2 (10 m) satellite products were used and tested against in situ data collected during three field-measurement campaigns in 2021 at eleven monitoring sites across Senegalese rangelands. Four statistical models were tested, namely, random forest, gradient boosting machines, and simple linear and multiple linear regressions. The two main vegetation mass variables modeled from remote sensing imagery were the standing herbaceous and litter dry mass (BH) and total forage dry mass (BT) with a dry mass of woody plant leaves added to BH. Overall, Sentinel-2 data provided the best performance for the assessment of BH with multiple linear regression (R 2 = 0.74; RMSE = 378 kg DM/ha) using NDI5 (Normalized Difference Index5), GRCI (Green Residue Cover Index), SRI (Simple Ratio Index), TCARI (Transformed Chlorophyll Absorption in Reflectance Index), and DFI (Dead Fuel Index) indices. For BT, the best model was also obtained from Sentinel-2 data, including RVI3 (Ratio Vegetation Index3) (R 2 = 0.78; RMSE = 496 kg DM/ha). Results showed the suitability of combining the red, green, blue, NIR, SWIR1, and SWIR2 bands in monitoring forage availability during the dry season. Our study revealed that the spectral richness of the optical sensor systems Sentinel-2, Landsat-8, and MODIS-MCD43A4 allowed for accurate assessments of dry-season forage mass of semi-arid rangelands. Adding to this, the high spatial and temporal resolution of Sentinel-2 satellite imagery makes this a promising data source for timely monitoring. These findings can support the monitoring of the animal feed balance in Sahelian countries and contribute to enhancing the resilience of pastoralism toward feed shortage through early warning systems.
Fichier principal
Vignette du fichier
2022_Mottet_fenvs-10-931299.pdf (2.79 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive

Dates and versions

hal-03844199 , version 1 (08-11-2022)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Adama Lo, Abdoul Aziz Diouf, Ibrahima Diedhiou, Cyrille Djitamagne Edouard Bassène, Louise Leroux, et al.. Dry season forage assessment across senegalese rangelands using earth observation data. Frontiers in Environmental Science, 2022, 10, 15p. ⟨10.3389/fenvs.2022.931299⟩. ⟨hal-03844199⟩
0 View
0 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More